Energy efficient mobile sink driven data collection in wireless sensor network with nonuniform data.

Area of Science:

• Computer Science
• Wireless Communication Networks

Background:

• Mobile sinks are crucial in wireless sensor networks (WSNs) for data collection and preventing hotspot issues.
• Non-uniform data generation and energy constraints pose significant challenges to data collection efficiency in WSNs.

Purpose of the Study:

• To propose an innovative approach, OCNTMS, for optimizing data collection in WSNs with non-uniform data generation and mobile sinks.
• To determine optimal rendezvous points and network topology for efficient data collection under energy constraints.

Main Methods:

• The OCNTMS approach utilizes weight-balanced clustering, cost function optimization, load-balanced link construction, and node forwarding selection.
• It focuses on efficiently constructing link sets within clusters and planning mobile sink traversal paths.

Main Results:

• OCNTMS demonstrated an 18% reduction in energy consumption.
• The proposed method increased network lifetime by 40% compared to existing approaches.
• Significant improvements in network energy efficiency and data transmission efficiency were observed.

Conclusions:

• OCNTMS effectively addresses the challenges of non-uniform data generation in mobile sink-driven WSNs.
• The approach enhances overall network performance by optimizing clustering and topology for energy efficiency and data collection.